Project

The Spread of True and False Information Online

Laboratory for Social Machines

We investigated the spread of all of the verified news stories–verified as either true or false–distributed on Twitter from 2006 to 2017.

With a data set of roughly 126K stories tweeted by around 3M people over 4.5M times, we classified news as true or false using information from six independent fact-checking organizations that exhibited 95-98% agreement on the classifications. False information  spread significantly farther, faster, deeper, and more broadly than the truth in all categories of information, and the effects were more pronounced for false political information than for false information about terrorism, natural disasters, science, urban legends, or financial information. We found that false information was more novel than true information, which suggests that people were more likely to share novel information. While false stories inspired fear, disgust, and surprise in replies, true stories inspired anticipation, sadness, joy, and trust.

Contrary to conventional wisdom, robots accelerated the spread of both true and false news at the same rate. This implies that false news spreads more than the truth because humans–not robots–are more likely to spread it.

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Research Topics
#social media